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A study on the effect of power transformation in the ARMA(p,q) model

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  • Key-Il Shin
  • Hee-Jeong Kang

Abstract

In time series analysis, the Box-Cox power transformation is generally used for variance stabilization. In this paper we show that the order and the first step ahead forecast of the transformed model are approximately invariant to those of the original model under certain assumptions on the mean and variance. A small Monte Carlo simulation is performed to support the results.

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  • Key-Il Shin & Hee-Jeong Kang, 2001. "A study on the effect of power transformation in the ARMA(p,q) model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(8), pages 1019-1028.
    • Handle: RePEc:taf:japsta:v:28:y:2001:i:8:p:1019-1028
    DOI: 10.1080/02664760120076689
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    References listed on IDEAS

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    1. Paul De Bruin & Philip Hans Franses, 1999. "Forecasting power-transformed time series data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(7), pages 807-815.
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